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AbstractBats are known to be reservoirs of several highly pathogenic viruses. Hence, the interest in bat virus discovery has been increasing rapidly over the last decade. So far, most studies have focused on a single type of virus detection method, either PCR, virus isolation or virome sequencing. Here we present a comprehensive approach in virus discovery, using all three discovery methods on samples from the same bats. By family-specific PCR screening we found sequences of paramyxoviruses, adenoviruses, herpesviruses and one coronavirus. By cell culture we isolated a novel bat adenovirus and bat orthoreovirus. Virome sequencing revealed viral sequences of ten different virus families and orders: three bat nairoviruses, three phenuiviruses, one orbivirus, one rotavirus, one orthoreovirus, one mononegavirus, five parvoviruses, seven picornaviruses, three retroviruses, one totivirus and two thymoviruses were discovered. Of all viruses identified by family-specific PCR in the original samples, none was found by metagenomic sequencing. Vice versa, none of the viruses found by the metagenomic virome approach was detected by family-specific PCRs targeting the same family. The discrepancy of detected viruses by different detection approaches suggests that a combined approach using different detection methods is necessary for virus discovery studies.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2, a new member of the genus Betacoronavirus, is a pandemic virus, which has caused numerous fatalities, particularly in the elderly and persons with underlying morbidities. At present, there are no approved vaccines nor antiviral therapies available. The detection and quantification of SARS-CoV-2-neutralizing antibodies plays a crucial role in the assessment of the immune status of convalescent COVID-19 patients, evaluation of recombinant therapeutic antibodies, and the evaluation of novel vaccines. To detect SARS-CoV-2-neutralizing antibodies, classically, a virus-neutralization test has to be performed at biosafety level 3, considerably limiting the general use of this test. In the present work, a biosafety level 1 pseudotype virus assay based on a propagation-incompetent vesicular stomatitis virus (VSV) has been used to determine the neutralizing antibody titers in convalescent COVID-19 patients. The neutralization titers in serum of two independently analyzed patient cohorts were available within 18 h and correlated well with those obtained with a classical SARS-CoV-2 neutralization test (Pearson correlation coefficients of r = 0.929 and r = 0.939, respectively). Most convalescent COVID-19 patients had only low titers of neutralizing antibodies (ND50 < 320). The sera of convalescent COVID-19 patients also neutralized pseudotype virus displaying the SARS-CoV-1 spike protein on their surface, which is homologous to the SARS-CoV-2 spike protein. In summary, we report a robust virus-neutralization assay, which can be used at low biosafety level 1 to rapidly quantify SARS-CoV-2-neutralizing antibodies in convalescent COVID-19 patients and vaccinated individuals.

A novel series of bis- (Abdelhamid et al., 2017, Banerjee et al., 2018, Bharanidharan et al., 2022)thiadiazoles was synthesized from the reaction of precursor dimethyl 2,2′-(1,2-diphenylethane-1,2-diylidene)-bis(hydrazine-1-carbodithioate) and hydrazonyl chlorides in ethanol under ultrasonic irradiation. Spectral tools (IR. NMR, MS, elemental analyses, molecular dynamic simulation, DFT and LUMO and HOMO) were used to elucidate the structure of the isolated products. Molecular docking for the precursor, 3 and ligands 6a-i to two COVID-19 important proteins M$^{pro}$ and RdRp was compared with two approved drugs, Remdesivir and Ivermectin. The binding affinity varied between the ligands and the drugs. The highest recorded binding affinity of 6c with M$^{pro}$ was (−9.2 kcal/mol), followed by 6b and 6a, (−8.9 and −8.5 kcal/mol), respectively. The lowest recorded binding affinity was (−7.0 kcal/mol) for 6 g. In comparison, the approved drugs showed binding affinity (−7.4 and −7.7 kcal/mol), for Remdesivir and Ivermectin, respectively, which are within the range of the binding affinity of our ligands. The binding affinity of the approved drug Ivermectin against RdRp recoded the highest (−8.6 kcal/mol), followed by 6a, 6 h, and 6i are the same have (−8.2 kcal/mol). The lowest reading was found for compound 3 ligand (−6.3 kcal/mol). On the other side, the amino acids also differed between the compounds studied in this project for both the viral proteins. The ligand 6a forms three H-bonds with Thr 319(A), Sr 255(A) and Arg 457(A), whereas Ivermectin forms three H-bonds with His 41(A), Gly143(A) and Gln 18(A) for viral M$^{pro}$. The RdRp amino acids residues could be divided into four groups based on the amino acids that interact with hydrogen or hydrophobic interactions. The first group contained 6d, 6b, 6 g, and Remdesivir with 1–4 hydrogen bonds and hydrophobic interactions 1 to 10. Group 2 is 6a and 6f exhibited 1 and 3 hydrogen bonds and 15 and 14 hydrophobic interactions. Group 3 has 6e and Ivermectin shows 4 and 3 hydrogen bonds, respectively and 11 hydrophobic interactions for both compounds. The last group contains ligands 3, 6c, 6 h, and 6i gave 1–3 hydrogen bonds and 6c and 3 recorded the highest number of hydrophobic interactions, 14 for both 6c and 6 h. Pro Tox-II estimated compounds’ activities as Hepatoxic, Carcinogenic and Mutagenic, revealing that 6f-h were inactive in all five similar to that found with Remdesivir and Ivermectin. The drug-likeness prediction was carried out by studying physicochemical properties, lipophilicity, size, polarity, insolubility, unsaturation, and flexibility. Generally, some properties of the ligands were comparable to that of the standards used in this study, Remdesivir and Ivermectin.

AbstractBackgroundCoronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the most suffering countries with the COVID-19 epidemic. It is important to predict the epidemics trend of COVID-19 epidemic in Italy to help develop public health strategies.MethodsWe used time-series data of COVID-19 from Jan 22,2020 to Mar 16,2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with similar total number of populations in Italy, was used as a comparative item.ResultsIn the eSIR model, we estimated that the basic reproductive number for COVID-19 was respectively 4.10 (95% CI: 2.15–6.77) in Italy and 3.15(95% CI: 1.71–5.21) in Hunan. There would be totally 30 086 infected cases (95%CI:7920-81 869) under the current country blockade and the endpoint would be Apr 25 (95%CI: Mar 30 to Aug 07) in Italy. If the country blockade is imposed 5 day later, the total number of infected cases would expand the infection scale 1.50 times.ConclusionItaly’s current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.

The outbreak of Coronavirus Disease (COVID-19) in Wuhan have affected more than 250 countries and regions worldwide. However, most of the clinical studies have been focused on Wuhan, and little is known about the disease outside of Wuhan in China. In this retrospective cohort study, we report the early clinical features of 80 patients with COVID-19 admitted to the hospital in Beijing. The results show that 27 (33.8%) patients had severe illness. Six (7.5%) patients were admitted to the ICU, and 3 (3.8%) patients died. Forty-eight percent (39/80) of the patients had a history of living/traveling in Wuhan. Patients with severe- illness were significantly older (average age, 71 years old vs 44 years old) and had a high incidence of expectoration (59.3% vs 34.0%), shortness of breath (92.6% vs 9.4%), anorexia (51.9% vs 18.9%) and confusion(18.5% vs 0%) compared with nonsevere patients. The systolic blood pressure (median, 130 mmHg vs 120 mmHg) was higher and the oxygen saturation (median, 98.3% vs 92.0%) was significantly lower in severe patients than nonsevere patients. In addition, myoglobin (median, 56.0 ng/mL vs 35.0 ng/mL), troponin I (median, 0.02 pg/mL vs 0.01 pg/mL), C-reactive protein (median, 69.7 mg/L vs 12.9 mg/L) and neutrophils (median, 3.3×109/L vs 2.2×109/L) were significantly increased, while lymphocytes (median, 0.8×109/L vs 1.2×109/L), albumin (mean, 32.8 g/L vs 36.8 g/L) and the creatinine clearance rate (median, 91.2 vs 108.2 ml/min/1.73m2) were significantly decreased among severe patients. Our study revealed that older patients with high levels of C-reactive protein, myoglobin, troponin I, and neutrophil and high systolic blood pressure as well as low levels of lymphocytes, and albumin and a low creatinine clearance rate and oxygen saturation were more likely to have severe disease.

Abstract An ongoing outbreak of 2019-nCoV pneumonia was first identified in Wuhan, Hubei province, China at the end of 2019. With the spread of the new coronavirus accelerating, person-to-person transmission in family homes or hospitals, and intercity spread of 2019-nCoV occurred. At least 40,261 cases confirmed, 23,589 cases suspected, 909 cases death and 3444 cases cured in China and worldwide 24 countries confirmed 383 cases being diagnosed, 1 case death in February 10th, 2020. At present, the mortality of 2019-nCoV in China is 2.3%, compared with 9.6% of SARS and 34.4% of MERS reported by WHO. It seems the new virus is not as fatal as many people thought. Chinese authorities improved surveillance network, made the laboratory be able to recognize the outbreak within a few weeks and announced the virus genome that provide efficient epidemiological control. More comprehensive information is required to understand 2019-nCoV feature, the epidemiology of origin and spreading, and the clinical phenomina. According to the current status, blocking transmission, isolation, protection, and alternative medication are the urgent management strategies against 2019-nCoV.

Abstract Background Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aide in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in haemodialysis (HD) patients are missing. Methods We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between March 3rd and July 3rd 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient haemodialysis units. We compared mortality among patients with and without COVID-19, matched for age, sex, and diabetes. Results During the observational period, 1 259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalised or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 (95% CI 80.6-359) to 342.7 (95% CI 60.6-13595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected mostly European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only (N = 22 826, AUCDev 0.64, AUCVal 0.69). The model for prediction of mortality was developed in all COVID-19 patients (AUCDev 0.71, AUCVal 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients. Conclusions We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. The current study can aid in the development of preventive strategies for future waves of COVID-19. Graphical Abstract Graphical Abstract

Up to April 4, 2020, the novel coronavirus disease-2019 COVID-19 has affected more than 1 099000 patients and has become a major global health concern. World Health Organization (WHO) has defined COVID-19 as a global pandemic. Critical care ultrasound (CCUS) can rapidly acquire the image of lung and other organs and demonstrate the pathophysiological changes to guide precise therapy in COVID-19 pneumonia without radiation or interfering with personal protective equipment. In addition, the application of CCUS can cover the whole courses from the fever clinic to the intensive care unit to improve the treatment. We would like to present the CCUS features about COVID-19 pneumonia and share the application experience of CCUS in Wuhan, China, and hope it works for physicians worldwide to solve the problem and improve the outcome.

AbstractThe ongoing outbreak of viral pneumonia in China and beyond is associated with a novel coronavirus, provisionally termed 2019-nCoV. This outbreak has been tentatively associated with a seafood market in Wuhan, China, where the sale of wild animals may be the source of zoonotic infection. Although bats are likely reservoir hosts for 2019-nCoV, the identity of any intermediate host facilitating transfer to humans is unknown. Here, we report the identification of 2019-nCoV related coronaviruses in pangolins (Manis javanica) seized in anti-smuggling operations in southern China. Metagenomic sequencing identified pangolin associated CoVs that belong to two sub-lineages of 2019-nCoV related coronaviruses, including one very closely related to 2019-nCoV in the receptor-binding domain. The discovery of multiple lineages of pangolin coronavirus and their similarity to 2019-nCoV suggests that pangolins should be considered as possible intermediate hosts for this novel human virus and should be removed from wet markets to prevent zoonotic transmission.

Electricity consumption has been affected due to worldwide lockdown policies against COVID-19. Many countries have pointed out that electricity supply security during the epidemic is critical to ensuring people’s livelihood. Accurate prediction of electricity demand would act a more important role in ensuring energy security for all the countries. Although there have been many studies on electricity forecasting, they did not consider the pandemic, and many works only considered the prediction accuracy and ignored the stability. Driven by the above reasons, it is necessary to develop an electricity consumption prediction model that can be well applied in the pandemic. In this work, a hybrid prediction system is proposed with data processing, modelling, and optimization. An improved complete ensemble empirical mode decomposition with adaptive noise is used for data preprocessing, which overcomes the shortcomings of the original method; a multi-objective optimizer is adopted for ensuring the accuracy and stability; support vector machine is used as the prediction model. Taking daily electricity demand of US as an example, the results prove that the proposed hybrid models are superior to benchmark models in both prediction accuracy and stability. Moreover, selection of input parameters is discussed, and the results indicate that the model considering the daily infections has the highest prediction accuracy and stability, and it is proved that the proposed model has great potential in real-world applications. Highlights • A hybrid model is developed for predicting daily electricity demand during COVID-19. • The accuracy and stability of the new model are higher than those of benchmark models. • The proposed model also performs well in multi-step prediction. • The model that only considers daily infections has the best prediction performance.